UCE-derived mitochondrial phylogeny reveals pervasive mito-nuclear discordances in serotine bats (genus Eptesicus) and complex evolutionary history in Eptesicus (Histiotus)
Bibliographic record
Abstract
Abstract Studies of evolution and biodiversity require solid understanding of species systematics revealed by molecular phylogeny using multilocus genomic data. Multilocus analyses, nevertheless, remain difficult in non-model taxa due to limited access to samples and molecular resources. To help overcome this limitation, ultra-conserved elements (UCEs) have been developed to generate large nuclear datasets and build more robust species phylogenies. Recently, MitoFinder pipeline was developed to further extract mitochondrial genes from the off-target sequences in UCE libraries to allow mito-nuclear comparison and increase the mitochondrial genomic database. Here we applied MitoFinder to published UCE datasets of serotine bats (genus Eptesicus ) and focused on E. (Histiotus) whose evolutionary history is poorly understood. Our results showed extensive mito-nuclear discordances in the divergence of major clades in Eptesicus and within E. (Histiotus) , indicating potential incomplete lineage sorting and historical mitochondrial introgression within and across subgenera. Moreover, we collected several new samples of E. (Histiotus) , including the first molecular data of the recently described E. (H) diaphanopterus , and combined available published sequences to generate the most taxa-complete mitochondrial phylogeny of E. (Histiotus) bats. Results supported the early divergence of E. (H.) magellanicus and the species status of E. (H.) diaphanopterus . In addition, we found strong evidence of cryptic diversity, with potentially new taxa in Peru, Uruguay, and Brazil, which needs to be evaluated in future studies using complementary data. Our study enriched the sequence database of serotine bats and shed light on the hidden diversity and complex evolutionary history of E. (Histiotus) .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".